The present invention relates to techniques for analysis of health care and pharmaceutical data. The invention in particular relates to the correlation of specific managed health care payers and plans with prescription data records that contain non-standardized health care payer and plan identifiers.
Prescription data records that are generated by retail pharmacies or hospital dispensaries, for example, when they fill prescriptions for customers, contain labels or data fields that include information identifying the party responsible for authorizing and/or making payments for the prescriptions. Useful market intelligence may be derived from statistical or other analysis of the responsible party information and other information in the prescription data records. The useful market intelligence may, for example, include competitive assessments of the marketing and sales of a particular product, which may be of interest to a pharmaceutical concern, or health care provider or agency.
The prescription data records may include information, which relates to the party responsible for authorizing and/or making payments, in one more data fields such as Bank Identification Numbers (“BINs”), Processor Control Numbers (“PCNs”), and health care plan Group Identification Numbers (“Group IDs”). The BIN data field may for example, contain a six-digit number that codes information about the adjudicator of the prescription drug claim or script.
Unfortunately, the type and number of such data fields may vary with each generator or source of the prescription data records. The prescription data records formats also may change in time. Further, the information in the data records is often coded in a non-standardized format. The labels and other coded information in the prescription data records must be decoded before full analysis of the data records can take place. In practice, a market research organization or other party analyzing the prescription data records may undertake to build a glossary or dictionary of the labels or codes that are found in data fields such BIN, PCN or Group ID.
The market research organization may manually verify the codes entered in the glossary or dictionary. On encountering a new label or code in a prescription data record, the market research organization may, for example, make manual inquires (e.g., via telephone calls) to individual retail pharmacy organizations or pharmacy benefit management companies (“PBMs”) in order to verify the meaning of the code. Such manual verification procedures can be both laborious and expensive. Furthermore, the manual verification procedures may not be always successful or complete. The success of the manual verification procedures depends on the responsiveness of the third parties, who may not be obligated to respond.
Consideration is now being given to ways of enhancing procedures for decoding information contained in prescription data records. Attention is directed to procedures for verifying the meaning of codes and labels in prescription data records that relate, for example, to the identity of parties responsible for authorizing and/or making payments. The desirable procedures may be automated, thereby minimizing the need to contact other parties for code verification.